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I built the same game on Roblox, Unity, and the web. Only one didn't fall apart.

Hugging Face Blog · Sep 29, 2025 · 2 min read · Read original article →

Curated by the Inblix editorial team


Featured image for article: I built the same game on Roblox, Unity, and the web. Only one didn't fall apart.

Andrej Karpathy’s ‘vibe coding’ concept—using AI as a high-level programming language where you barely touch the code—sounds like magic for game development. It kind of is, right up until the project hits a few hundred lines. Then the context window fills up, model performance degrades, and your game turns into digital spaghetti.

That’s the core problem VibeGame’s creator ran into while testing AI-driven game development across three platforms. The experiment was straightforward: build the same incremental game, inspired by Grass Cutting Incremental, using Claude Code on Roblox, Unity, and a bare-bones web stack. The results weren’t close.

Roblox’s official MCP server offered beautiful high-level abstractions—AI instantly grasped the syntax—but the walled garden killed it. No file system access meant no real context management. Unity’s unofficial MCP was the opposite problem: full file access, but the engine’s endless ways to accomplish the same task, which shift constantly across versions, left the AI confused and unreliable. “There are many ways to do everything in Unity,” the developer noted, which means you spend more time specifying how to do things than what to do.

The web stack—three.js for rendering, rapier for physics, bitecs for game logic—blew both away in AI performance. The reason is obvious: massive training data from web development. But there’s a catch. These libraries are so low-level that you end up building an engine before you can build a game. The fix was creating a custom high-level abstraction layer on top, essentially an AI-native game framework that keeps projects lean enough to fit in a model’s context window.

To manage what context remains, the developer built Shallot, a lightweight system for Claude Code with two commands: /peel to load context at the start of a conversation, and /nourish to update it at the end. It’s dead simple and intentionally unopinionated. The bigger lesson here isn’t about any single tool. It’s that vibe coding games demands a platform that enforces discipline—high-level abstractions the AI understands well, minimal boilerplate, and a project structure that doesn’t metastasize. Right now, that platform doesn’t quite exist off the shelf. But the blueprint is getting clearer.

💡 Key Takeaways

  1. AI model performance degrades as context windows fill up, which happens fast in game development and is the primary bottleneck for vibe coding.
  2. Roblox and Unity both failed practical vibe coding tests: Roblox due to its walled garden blocking file access, Unity because its complexity and inconsistent APIs confused the AI.
  3. A plain web stack with three.js delivered the best AI code generation out of the box, but its low-level nature forced the developer to build a custom abstraction layer first.
  4. The developer open-sourced Shallot, a lightweight Claude Code context management tool that uses two commands to load and update project context between sessions.

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